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ENH: Allow genfromtxt to unpack structured arrays (#16650)
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* ENH: Allow genfromtxt to unpack structured arrays

genfromtxt failed to transpose output when
unpack=True and `dtype` was structured (or None).
This patch resolves the issue by
returning a list of arrays, as in `loadtxt`.

Co-authored-by: Matti Picus <matti.picus@gmail.com>
Co-authored-by: Eric Wieser <wieser.eric@gmail.com>
Co-authored-by: Sebastian Berg <sebastian@sipsolutions.net>
Co-authored-by: Ross Barnowski <rossbar@berkeley.edu>
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5 people committed Sep 11, 2020
1 parent 02798e4 commit 3329d26
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16 changes: 16 additions & 0 deletions doc/release/upcoming_changes/16650.compatibility.rst
@@ -0,0 +1,16 @@
`numpy.genfromtxt` now correctly unpacks structured arrays
----------------------------------------------------------
Previously, `numpy.genfromtxt` failed to unpack if it was called with
``unpack=True`` and a structured datatype was passed to the ``dtype`` argument
(or ``dtype=None`` was passed and a structured datatype was inferred).
For example::

>>> data = StringIO("21 58.0\n35 72.0")
>>> np.genfromtxt(data, dtype=None, unpack=True)
array([(21, 58.), (35, 72.)], dtype=[('f0', '<i8'), ('f1', '<f8')])

Structured arrays will now correctly unpack into a list of arrays,
one for each column::

>>> np.genfromtxt(data, dtype=None, unpack=True)
[array([21, 35]), array([58., 72.])]
22 changes: 17 additions & 5 deletions numpy/lib/npyio.py
Expand Up @@ -815,8 +815,9 @@ def loadtxt(fname, dtype=float, comments='#', delimiter=None,
fourth column the same way as ``usecols = (3,)`` would.
unpack : bool, optional
If True, the returned array is transposed, so that arguments may be
unpacked using ``x, y, z = loadtxt(...)``. When used with a structured
data-type, arrays are returned for each field. Default is False.
unpacked using ``x, y, z = loadtxt(...)``. When used with a
structured data-type, arrays are returned for each field.
Default is False.
ndmin : int, optional
The returned array will have at least `ndmin` dimensions.
Otherwise mono-dimensional axes will be squeezed.
Expand Down Expand Up @@ -1640,7 +1641,9 @@ def genfromtxt(fname, dtype=float, comments='#', delimiter=None,
If 'lower', field names are converted to lower case.
unpack : bool, optional
If True, the returned array is transposed, so that arguments may be
unpacked using ``x, y, z = loadtxt(...)``
unpacked using ``x, y, z = genfromtxt(...)``. When used with a
structured data-type, arrays are returned for each field.
Default is False.
usemask : bool, optional
If True, return a masked array.
If False, return a regular array.
Expand Down Expand Up @@ -2269,9 +2272,18 @@ def encode_unicode_cols(row_tup):
if usemask:
output = output.view(MaskedArray)
output._mask = outputmask
output = np.squeeze(output)
if unpack:
return output.squeeze().T
return output.squeeze()
if names is None:
return output.T
elif len(names) == 1:
# squeeze single-name dtypes too
return output[names[0]]
else:
# For structured arrays with multiple fields,
# return an array for each field.
return [output[field] for field in names]
return output


_genfromtxt_with_like = array_function_dispatch(
Expand Down
47 changes: 46 additions & 1 deletion numpy/lib/tests/test_io.py
Expand Up @@ -1026,7 +1026,7 @@ def test_empty_field_after_tab(self):
a = np.array([b'start ', b' ', b''])
assert_array_equal(x['comment'], a)

def test_structure_unpack(self):
def test_unpack_structured(self):
txt = TextIO("M 21 72\nF 35 58")
dt = {'names': ('a', 'b', 'c'), 'formats': ('|S1', '<i4', '<f4')}
a, b, c = np.loadtxt(txt, dtype=dt, unpack=True)
Expand Down Expand Up @@ -2358,6 +2358,51 @@ def test_auto_dtype_largeint(self):
assert_equal(test['f1'], 17179869184)
assert_equal(test['f2'], 1024)

def test_unpack_structured(self):
# Regression test for gh-4341
# Unpacking should work on structured arrays
txt = TextIO("M 21 72\nF 35 58")
dt = {'names': ('a', 'b', 'c'), 'formats': ('S1', 'i4', 'f4')}
a, b, c = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_equal(a.dtype, np.dtype('S1'))
assert_equal(b.dtype, np.dtype('i4'))
assert_equal(c.dtype, np.dtype('f4'))
assert_array_equal(a, np.array([b'M', b'F']))
assert_array_equal(b, np.array([21, 35]))
assert_array_equal(c, np.array([72., 58.]))

def test_unpack_auto_dtype(self):
# Regression test for gh-4341
# Unpacking should work when dtype=None
txt = TextIO("M 21 72.\nF 35 58.")
expected = (np.array(["M", "F"]), np.array([21, 35]), np.array([72., 58.]))
test = np.genfromtxt(txt, dtype=None, unpack=True, encoding="utf-8")
for arr, result in zip(expected, test):
assert_array_equal(arr, result)
assert_equal(arr.dtype, result.dtype)

def test_unpack_single_name(self):
# Regression test for gh-4341
# Unpacking should work when structured dtype has only one field
txt = TextIO("21\n35")
dt = {'names': ('a',), 'formats': ('i4',)}
expected = np.array([21, 35], dtype=np.int32)
test = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_array_equal(expected, test)
assert_equal(expected.dtype, test.dtype)

def test_squeeze_scalar(self):
# Regression test for gh-4341
# Unpacking a scalar should give zero-dim output,
# even if dtype is structured
txt = TextIO("1")
dt = {'names': ('a',), 'formats': ('i4',)}
expected = np.array((1,), dtype=np.int32)
test = np.genfromtxt(txt, dtype=dt, unpack=True)
assert_array_equal(expected, test)
assert_equal((), test.shape)
assert_equal(expected.dtype, test.dtype)


class TestPathUsage:
# Test that pathlib.Path can be used
Expand Down

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